Fuzzy-Logic Applications in Electric Drives and Power Electronics
Abdul R. Ofoli The University of Tennessee at Chattanooga, Chattanooga, TN, United States
The use of an extended Kalman filter to train fuzzy neural network structures for online speed trajectory tracking of a brushless drive system is illustrated as an alternative to control schemes. Also described in this chapter is an implementation of a genetic-based hybrid fuzzy-proportional-integral-derivative (PID) controller for industrial motor drives. The genetic optimization technique is used to determine the optimal values of the scaling factors of the output variables of the fuzzy-PID (FPID) controller. The objective is to utilize the best attributes of the PID and ...
Get Power Electronics Handbook, 4th Edition now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.